Quantifying the Effect of Cyclist Behavior on Bicycle Crashes and Fatalities

This paper is dedicated to quantifying the effect of cyclist riding behavior in bicycle crashes, injuries and fatalities. The motivation of the paper comes from the New York City (NYC) Vision Zero program and moreover aims to fill the literature gap that misses the consideration of cyclist behavior in existing crash models. The quantification is done by the introduction of three regression models for Manhattan in NYC. The first two relate cyclist behavior to crash counts and crash rates; the third relates behavior to fatality equivalent counts. Results show that riding counter flow in a bicycle lane is the largest cause of crashes while riding in a lane other than the bike lane or the one adjacent to it is the largest cause for fatality equivalent counts. Other measures are also quantified, namely the use of helmets and area specific effects. The latter shows that crashes are more likely to happen in the area around the Central Park (Upper West and Upper East Manhattan), whereas the built environment in Midtown is very safe for bikes. Moreover, a helmet-use sensitivity analysis is presented showing that helmets can aid in decreasing fatality equivalent counts by up to 60% from current use. Finally, the use of the quantifications for severity-based fine pricing is introduced.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Kasm, Omar Abou
    • Ma, Ziyi
    • Chow, Joseph Y J
    • Diabat, Ali
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01697900
  • Record Type: Publication
  • Report/Paper Numbers: 19-00054
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:41AM